About Foglift: AI Visibility, Audits, Crawlers + API
Foglift is an AI-search visibility platform for startups and agencies. It combines unlimited single-page Technical Audits at $0 with five-engine answer monitoring from $49 per month, crawler and referral analytics, plus API, CLI, and MCP access.
The product keeps four kinds of evidence separate: whether a page is technically ready, whether an AI answer mentions or cites the brand, whether an AI crawler requested the page, and whether a person arrived from an AI answer. A crawler fetch is diagnostic. It is never counted as a citation or a human referral.
Teams use that evidence loop to move from a weak page or buyer prompt to a specific fix, then recheck the same outcome. Technical Audits cover SEO, AI Readiness, performance, security, and accessibility. AI Visibility monitoring records prompt-level mentions, positions, sentiment, competitors, and provider-returned citations across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overview.
What we do
- ✓Technical Audits covering SEO, AI Readiness, performance, security, and accessibility
- ✓AI Visibility monitoring across ChatGPT, Perplexity, Google AI Overview, Gemini, and Claude
- ✓Prompt discovery, recommendations, and content briefs tied to measured evidence
- ✓Competitor, sentiment, citation, crawler, and AI referral tracking
- ✓REST API, CLI, MCP, and webhook access on Launch and higher plans
Developers can plug Foglift directly into their stack via the REST API, the CLI, or the Foglift MCP server, available as a hosted OAuth connection or local package for supported agent clients.
How the Foglift evidence loop works
Each layer answers a different question. Keeping those answers separate prevents a crawler request or a healthy page score from being mistaken for visibility in a real AI answer.
| Evidence layer | What it measures | Decision it supports |
|---|---|---|
| Technical Audit | SEO, AI Readiness, performance, security, and accessibility | What should change on this page? |
| AI Visibility | Mentions, positions, sentiment, competitors, and returned citations | Does an engine include the brand in its answer? |
| Crawler analytics | Verified requests grouped by crawler and purpose | Which pages are engines requesting? |
| AI referrals | Human visits attributed to AI-answer sources | Which answers send people to the site? |
| Recommendations | Evidence-ranked fixes and prompt opportunities | What is the next highest-impact action? |
Built for teams
Startups use Foglift to connect technical site health with answer-level brand visibility in one operating view. Agencies can add multiple brands and team members, then use the branded Client Portal on Growth or full white-label delivery on Enterprise. Launch starts at $49 per month for up to three brands and three team members. It includes all five engines, daily monitoring, REST API, CLI, MCP, and webhook access.
By the numbers
5
Technical Audit dimensions
5
AI engines monitored
28
AI crawlers checked
$49
Launch plan per month
Evidence rules we do not collapse
- Search access and model training are different.
- OpenAI documents OAI-SearchBot, GPTBot, and ChatGPT-User as separate controls for search, training, and user-requested visits. Read OpenAI's crawler reference.
- Crawler identity and purpose stay distinct.
- Anthropic publishes separate controls for Claude-SearchBot, ClaudeBot, and Claude-User. Foglift records those agents separately instead of treating every request as the same signal. Read Anthropic's crawler guidance.
- Eligibility does not guarantee inclusion.
- Google applies its normal Search eligibility requirements to AI features and does not guarantee that an eligible page will appear. Foglift therefore reports technical readiness separately from measured answer visibility. Read Google's AI feature guidance.
Try our AEO-focused tools
The free utilities inspect specific on-page inputs, including schema structure, entity identity, metadata, and crawler policy. They diagnose whether the published page is easier to parse. They do not promise that an AI engine will mention or cite it.
- →Schema Generator. Build JSON-LD with a Foglift AI Pickup Score for each schema, including SoftwareApplication and Article citation fields most generators skip.
- →Structured Data AI Pickup Validator. Goes beyond Google's Rich Results Test to flag the patterns AI engines actually deprioritize: unnamed nested entities, over-nesting, missing entity disambiguation.
- →Meta Tag Analyzer. Inspect Open Graph, Twitter, and canonical tags with AI-engine-specific guidance on what to fix.
Our approach
Foglift is built by a small, focused team that believes the best tools are simple, fast, and transparent. We ship weekly, listen to feedback obsessively, and keep pricing explicit. Every plan includes unlimited single-page Technical Audits. Active Free accounts monitor Perplexity weekly, while Launch adds daily monitoring across all five engines plus REST API, CLI, MCP, and webhook access for $49 per month.
Frequently asked questions
What does Foglift measure?
Which AI engines does Foglift monitor?
Can I use Foglift for free?
Who is Foglift built for?
See what we've shipped recently on our changelog, or check our roadmap to see what's coming next.